Distributed Data Exchange with Leap Motion

Abstract

Collaborative virtual environments can connect people in social virtual spaces even when they are geographically distant from each other. Hand interactions are fundamental to enable natural collaboration and immersive experiences as they are a visually intuitive means of communication. However, scalability is challenging as numerous participants typically produce a large volume of visualisation data that may overload a single node if the management is centralised. In this paper we propose a transmission strategy where the high-throughput visualisation data (e.g. hand joints) is exchanged amongst participants in a distributed fashion. We use a level-of-detail strategy to further reduce the network traffic accounting for spatial distances amongst participants in the virtual space. We design an experiment where we analyse the network traffic in a virtual environment with up to seven participants whose hands are tracked using Leap Motion. We show that the proposed method can effectively reduce the network traffic of visualisation data when compared to a centralised approach.

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